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In order to estimate the location of an indoor mobile station (MS), estimated time-of-arrival (TOA) can be obtained at each of several access points (APs). These TOA estimates can then be used to solve for the location of the MS. Alternatively, it is possible to estimate the location of the MS directly by incorporating the received signals at all APs in a direct estimator of position. This article presents a deeper analysis of a previously proposed maximum likelihood (ML)-TOA estimator, including a uniqueness property and the behavior in nonline-of-sight (NLOS) situations. Then, a ML direct location estimation technique utilizing all received signals at the various APs is proposed based on the ML-TOA estimator. The Cramer-Rao lower bound (CRLB) is used as a performance reference for the ML direct location estimator.

Indoor positioning based on statistical multipath channel modeling